Just a basic example of loading a baseline Lasso model without validation. Putting this here for students who just need to load up the Boston Housing dataset and start building a basic regression pipeline.

lasso_mse_paths.py

from sklearn.linear_model import ElasticNetCV
from sklearn.datasets import load_boston

data = load_boston()
df = pd.DataFrame(data['data'], columns=data['feature_names'])

X, y = df, data['target']

elastic = ElasticNetCV(cv=5)
model = elastic.fit(X, y )

pd.DataFrame(model.mse_path_).plot()